Exploring How System Dynamics Models Can Be Adapted to Analyze Climate-Related Feedback Loops and Policy Impacts

The growing urgency of climate change has intensified the need for robust modeling tools capable of capturing complex, dynamic interactions across environmental, economic, and social systems. System Dynamics (SD) models have emerged as a powerful framework for simulating climate-related feedback loops and informing long-term policy decisions. This scoping review critically examines the current state of SD modeling in climate policy, with a particular focus on its strengths, limitations, and potential for integration with other modeling paradigms. While SD models excel at illustrating dynamic processes and system-wide interactions, they still have limitations in representing nonlinear feedback, tipping points, and cross-sectoral dependencies. Recent advancements have improved the modeling of complex climate feedback and scenario exploration; however, challenges persist in terms of model transparency, empirical data integration, and stakeholder inclusivity. The review identifies key opportunities to enhance SD models through modular design, better parameterization, and hybridization with agent-based and Earth system models. It also underscores the importance of interdisciplinary collaboration and the development of open-access model libraries. By addressing these gaps, SD modeling can play a more prominent role in shaping resilient and adaptive climate policies. This work contributes to a growing body of literature advocating systems-based approaches to climate governance, highlighting actionable pathways to enhance the credibility, utility, and impact of SD models in climate research and decision-making.